Robust optimization is an emerging area in research that allows addressing different
optimization problems and specifically industrial optimization problems where there is a …

Most of the optimization problems encountered in the real world are discrete type which
involves decision variables defined in the discrete search space. Binary optimization …

The progress of metaheuristic techniques, big data, and the Internet of things generates
opportunities to performance improvements in complex industrial systems. This article …

Facility Location Problems (FLPs) aim to determine the most suitable location for the desired
facility given the problem constraints. The sheer variety of facility types in the modern era …

The binarization of continuous swarm-intelligence metaheuristics is an area of great interest
in operational research. This interest is mainly due to the application of binarized …

Method: One of the main problems which we turn out to be faced on having used
metaheuristic is the difficulty of realizing a correct parametrization with the purpose to find …

This article evaluates the efficiency of three meta-heuristic optimiser (viz. MOGA-II, MOPSO
and NSGA-II)-based solution methods for designing a sustainable three-echelon distribution …

Different criteria exist for the classification of the metaheuristics. One important classification
is: improvement metaheuristics and constructive. On the one hand improvement …

In engineering and science, there are many combinatorial optimization problems. A lot of
these problems are NP-hard and can hardly be addressed by full techniques. Therefore …

Many of the problems addressed at the industrial level are of a combinatorial type and a sub-
assembly not less than these are of the NP-hard type. The design of algorithms that solve …